Reconstructing Cosmic Velocities with the Kinetic Sunyaev-Zeldovich Effect

Over the last few decades, Physical Cosmology has come a long way from a primitive and data-deprived field of research with several speculative theories of origin, evolution, and composition of the Universe to a mature, data-driven field of research with a very well-established theoretical foundation. The Standard Model of Cosmology, the 6-parameter $\Lambda$CDM model, has been immensely successful in describing most (but not all) of what we see around us in the observable Universe. Tested against various independent cosmological probes like the Cosmic Microwave Background (CMB), Large-Scale Structure (LSS), Lyman-alpha forest, supernovae datasets, etc, the model has proven to be pretty concordant. However, there still remain several tantalizing open questions about our universe which have kept cosmologists occupied. Our progress in answering these questions is usually a matter of gleaning more and more information about our universe. This is done either by finding new probes, acquiring more data for existing probes, or by improving statistical methodologies employed to existing probes and datasets. The first part of this thesis develops and explores the use of the kinetic Sunyaev-Zeldovich (kSZ) effect as a cosmological probe. After giving a brief overview of the field in an introductory chapter, a theoretical framework for the study of the kSZ effect is laid out in chapter 2. We propose an optimal bispectrum estimator that combines CMB maps with galaxy surveys and show its equivalence to existing statistics. We explore the information content of the estimator, generalize it to incorporate issues arising from redshift uncertainties in photometric surveys and redshift space distortions, and produce forecasts for upcoming CMB experiments and galaxy surveys. Chapter 3 explores kSZ velocity reconstruction --- a quadratic estimator for mapping the largest-scale cosmological modes of the Universe. We implement kSZ velocity reconstruction in an N-body simulation pipeline and explore its properties. We find that the reconstruction noise can be larger than the analytic prediction which is usually assumed. We revisit the analytic prediction and find additional noise terms which explain the discrepancy. The new terms are obtained from a six-point halo model calculation and are analogous to the $N^{(1)}$ and $N^{(3/2)}$ biases in CMB lensing. We implement an MCMC pipeline which estimates $f_{NL}$ from N-body kSZ simulations and show that it recovers unbiased estimates of $f_{NL}$, with statistical errors consistent with a Fisher matrix forecast. Overall, these results confirm that kSZ velocity reconstruction will be a powerful probe of cosmology in the near future, but new terms should be included in the noise power spectrum. The second part of the thesis presents my contribution to the CHIME/FRB collaboration where we are searching for Fast Radio Bursts (FRB). FRBs are bright, millisecond pulses of extra-galactic origin which were first seen in 2007 in a radio survey, with another handful of them seen in the ensuing decade. A tracer of large-scale structure, FRBs offer a new window into the Universe and are sensitive to many astrophysically relevant quantities. The CHIME/FRB experiment which was commissioned in 2018, is currently the leading experiment cataloging and studying these FRBs. I developed a Markov Chain Monte Carlo pipeline that fits models of varying complexity to the FRB events observed by CHIME

KSZ tomography and the bispectrum

Several statistics have been proposed for measuring the kSZ effect by combining the small-scale CMB with galaxy surveys. We review five such statistics, and show that they are all mathematically equivalent to the optimal bispectrum estimator of type $\langle ggT \rangle$. Reinterpreting these kSZ statistics as special cases of bispectrum estimation makes many aspects transparent, for example optimally weighting the estimator, or incorporating photometric redshift errors. We analyze the information content of the bispectrum and show that there are two observables: the small-scale galaxy-electron power spectrum $P_{ge}(k_S)$, and the large-scale galaxy-velocity power spectrum $P_{gv}(k)$. The cosmological constraining power of the kSZ arises from its sensitivity to fluctuations on large length scales, where its effective noise level can be much better than galaxy surveys.Comment: 39 page

Comprehensive Bayesian analysis of FRB-like bursts from SGR 1935+2154 observed by CHIME/FRB

The bright millisecond-duration radio burst from the Galactic magnetar SGR 1935+2154 in 2020 April was a landmark event, demonstrating that at least some fast radio burst (FRB) sources could be magnetars. The two-component burst was temporally coincident with peaks observed within a contemporaneous short X-ray burst envelope, marking the first instance where FRB-like bursts were observed to coincide with X-ray counterparts. In this study, we detail five new radio burst detections from SGR 1935+2154, observed by the CHIME/FRB instrument between October 2020 and December 2022. We develop a fast and efficient Bayesian inference pipeline that incorporates state-of-the-art Markov chain Monte Carlo techniques and use it to model the intensity data of these bursts under a flexible burst model. We revisit the 2020 April burst and corroborate that both the radio sub-components lead the corresponding peaks in their high-energy counterparts. For a burst observed in 2022 October, we find that our estimated radio pulse arrival time is contemporaneous with a short X-ray burst detected by GECAM and HEBS, and Konus-Wind and is consistent with the arrival time of a radio burst detected by GBT. We present flux and fluence estimates for all five bursts, employing an improved estimator for bursts detected in the side-lobes. We also present upper limits on radio emission for X-ray emission sources which were within CHIME/FRB's field-of-view at trigger time. Finally, we present our exposure and sensitivity analysis and estimate the Poisson rate for FRB-like events from SGR 1935+2154 to be $0.005^{+0.082}_{-0.004}$ events/day above a fluence of $10~\mathrm{kJy~ms}$ during the interval from 28 August 2018 to 1 December 2022, although we note this was measured during a time of great X-ray activity from the source.Comment: 22 pages, 6 figures, 4 tables. To be submitted to Ap

CHIME/FRB Discovery of 25 Repeating Fast Radio Burst Sources

We present the discovery of 25 new repeating fast radio burst (FRB) sources found among CHIME/FRB events detected between 2019 September 30 and 2021 May 1. The sources were found using a new clustering algorithm that looks for multiple events co-located on the sky having similar dispersion measures (DMs). The new repeaters have DMs ranging from $\sim$220 pc cm$^{-3}$ to $\sim$1700 pc cm$^{-3}$, and include sources having exhibited as few as two bursts to as many as twelve. We report a statistically significant difference in both the DM and extragalactic DM (eDM) distributions between repeating and apparently nonrepeating sources, with repeaters having lower mean DM and eDM, and we discuss the implications. We find no clear bimodality between the repetition rates of repeaters and upper limits on repetition from apparently nonrepeating sources after correcting for sensitivity and exposure effects, although some active repeating sources stand out as anomalous. We measure the repeater fraction and find that it tends to an equilibrium of $2.6_{-2.6}^{+2.9}$% over our exposure thus far. We also report on 14 more sources which are promising repeating FRB candidates and which merit follow-up observations for confirmation.Comment: Submitted to ApJ. Comments are welcome and follow-up observations are encouraged

Sub-second periodicity in a fast radio burst

Fast radio bursts (FRBs) are millisecond-duration flashes of radio waves that are visible at distances of billions of light-years. The nature of their progenitors and their emission mechanism remain open astrophysical questions. Here we report the detection of the multi-component FRB 20191221A and the identification of a periodic separation of 216.8(1) ms between its components with a significance of 6.5 sigmas. The long (~3 s) duration and nine or more components forming the pulse profile make this source an outlier in the FRB population. Such short periodicity provides strong evidence for a neutron-star origin of the event. Moreover, our detection favours emission arising from the neutron-star magnetosphere, as opposed to emission regions located further away from the star, as predicted by some models.Comment: Updated to conform to the accepted versio

Robust Neural Network-Enhanced Estimation of Local Primordial Non-Gaussianity

When applied to the non-linear matter distribution of the universe, neural networks have been shown to be very statistically sensitive probes of cosmological parameters, such as the linear perturbation amplitude $\sigma_8$. However, when used as a "black box", neural networks are not robust to baryonic uncertainty. We propose a robust architecture for constraining primordial non-Gaussianity $f_{NL}$, by training a neural network to locally estimate $\sigma_8$, and correlating these local estimates with the large-scale density field. We apply our method to N-body simulations, and show that $\sigma(f_{NL})$ is 3.5 times better than the constraint obtained from a standard halo-based approach. We show that our method has the same robustness property as large-scale halo bias: baryonic physics can change the normalization of the estimated $f_{NL}$, but cannot change whether $f_{NL}$ is detected

Constraining fNLf_{NL} using the Large-Scale Modulation of Small-Scale Statistics

We implement a novel formalism to constrain primordial non-Gaussianity of the local type from the large-scale modulation of the small-scale power spectrum. Our approach combines information about primordial non-Gaussianity contained in the squeezed bispectrum and the collapsed trispectrum of large-scale structure together in a computationally amenable and consistent way, while avoiding the need to model complicated covariances of higher $N$-point functions. This work generalizes our recent work, which used a neural network estimate of local power, to the more conventional local power spectrum statistics, and explores using both matter field and halo catalogues from the Quijote simulations. We find that higher $N$-point functions of the matter field can provide strong constraints on $f_{NL}$, but higher $N$-point functions of the halo field, at the halo density of Quijote, only marginally improve constraints from the two-point function.Comment: 14 pages, 7 figure

Pre-equilibrium particle emission due to heavy and light ion interactions

580-583To understand the mechanism of pre-equilibrium particle emission using light and heavy ion beams with different targets at energy above the Coulomb barrier, a study has been done. The cross-sections for twelve systems 4He + 59Co, 4He +124Sn, 4He + 165Ho, 12C + 59Co, 12C +124Sn, 12C + 165Ho, 16O + 59Co, 16O + 124Sn, 16O + 165Ho, 19F + 59Co, 19F + 124Sn and 19F + 165Ho have been calculated using the statistical model code ALICE-91. Significant pre-equilibrium particle emission contribution has been obtained for lighter systems at higher projectile energy. It has also been found that the pre-equilibrium particle emission affects predominantly over the equilibrated compound nucleus emissions at high projectile energies. Pre-equilibrium fraction (FPEQ) has been deduced from the excitation function data for different systems at different projectile energies. The present results indicate that the probability of pre-equilibrium particle emission depends not only on a single entrance channel parameter, but it also depends on various entrance channel parameters, namely: projectile energy, mass of the projectile, mass of the target and entrance-channel mass asymmetry. The present analysis of the data also suggests that the pre-equilibrium particle emission contributes significantly at higher projectile energy for lighter mass projectile and target

Biomarker-focused multi-drug combination therapy and repurposing trial in mdx mice.

Duchenne muscular dystrophy is initiated by dystrophin deficiency, but downstream pathophysiological pathways such as membrane instability, NFĸB activation, mitochondrial dysfunction, and induction of TGFβ fibrosis pathways are thought to drive the disability. Dystrophin replacement strategies are hopeful for addressing upstream dystrophin deficiency; however, all methods to date use semi-functional dystrophin proteins that are likely to trigger downstream pathways. Thus, combination therapies that can target multiple downstream pathways are important in treating DMD, even for dystrophin-replacement strategies. We sought to define blood pharmacodynamic biomarkers of drug response in the mdx mouse model of Duchenne muscular dystrophy using a series of repurposed drugs. Four-week-old mdx mice were treated for four weeks with four different drugs singly and in combination: vehicle, prednisolone, vamorolone, rituximab, β-aminoisobutyric acid (BAIBA) (11 treatment groups; n = 6/group). Blood was collected via cardiac puncture at study termination, and proteomic profiling was carried out using SOMAscan aptamer panels (1,310 proteins assayed). Prednisolone was tested alone and in combination with other drugs. It was found to have a good concordance of prednisolone-responsive biomarkers (56 increased by prednisolone, 39 decreased) focused on NFκB and TGFβ cascades. Vamorolone shared 45 (80%) of increased biomarkers and 13 (33%) of decreased biomarkers with prednisolone. Comparison of published human corticosteroid-responsive biomarkers to our mdx data showed 14% (3/22) concordance between mouse and human. Rituximab showed fewer drug-associated biomarkers, with the most significant being human IgG. On the other hand, BAIBA treatment (high and low dose) showed a drug-associated increase in 40 serum proteins and decreased 5 serum proteins. Our results suggest that a biomarker approach could be employed for assessing drug combinations in both mouse and human studies